Our proposed Hand De-occlusion and Removal (HDR) framework is simple, flexible, and effective. Extensive experiments on the well-known InterHand2.6M benchmark [1]} show that our method significantly outperforms the state-of-the-art 3D interacting hand pose estimation systems. Our framework builds upon the latest research progress of amodal segmentation [2]}, de-occlusion [3]}, [4]}, [5]}, and 3D single-hand pose estimation [6]}. Note that, we do not perform complete comparisons with previous amodal segmentation, de-occlusion, and SHPE approaches. We also do not claim any algorithmic superiority concerning model architecture design. Because our aim is to propose a framework to solve the challenges of 3D interacting hand pose estimation. And designing powerful modules to improve the performance of amodal segmentation, de-occlusion, and SHPE is not the focus of this paper.
